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  • Open Access

    ARTICLE

    Software Reliability Assessment Using Hybrid Neuro-Fuzzy Model

    Parul Gandhi1, Mohammad Zubair Khan2, Ravi Kumar Sharma3, Omar H. Alhazmi2, Surbhi Bhatia4,*, Chinmay Chakraborty5

    Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943

    Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software reliability. The proposed algorithm is… More >

  • Open Access

    ARTICLE

    Ground Nephogram Enhancement Algorithm Based on Improved Adaptive Fractional Differentiation

    Xiaoying Chen1,*, Jie Kang1, Cong Hu2

    Journal of New Media, Vol.3, No.4, pp. 151-180, 2021, DOI:10.32604/jnm.2021.024665

    Abstract The texture of ground-based nephogram is abundant and multiplicity. Many cloud textures are not as clear as artificial textures. A nephogram enhancement algorithm based on Adaptive Fractional Differential is established to extract the natural texture of visible ground-based cloud image. GrunwaldLentikov (G-L) and Grunwald-Lentikov (R-L) fractional differential operators are applied to the enhancement algorithm of ground-based nephogram. An operator mask based on adaptive differential order is designed. The corresponding mask template is used to process each pixel. The results show that this method can extract image texture and edge details and simplify the process of differential order selection. More >

  • Open Access

    ARTICLE

    Blockchain-Based Decentralized Reputation Management System for Internet of Everything in 6G-Enabled Cybertwin Architecture

    Meimin Wang, Zhili Zhou*, Chun Ding

    Journal of New Media, Vol.3, No.4, pp. 137-150, 2021, DOI:10.32604/jnm.2021.024543

    Abstract Internet of Everything (IoE) has emerged as a promising paradigm for the purpose of connecting and exchanging data among physical objects and humans over the Internet, and it can be widely applied in the fields of industry, transportation, commerce, and education. Recently, the emergence of 6G-enabled cybertwin network architecture provides the technical and theoretical foundation for the realization of IoE paradigm. However, the IoE has three open issues in the 6G-enabled cybertwin architecture, i.e., data authenticity, data storage and node reliability. To address these issues, we propose a blockchain-based decentralized reputation management system (BC-DRMS) for IoE in 6G-enabled Cybertwin architecture.… More >

  • Open Access

    REVIEW

    Review of Unsupervised Person Re-Identification

    Yang Dai*, Zhiyuan Luo

    Journal of New Media, Vol.3, No.4, pp. 129-136, 2021, DOI:10.32604/jnm.2021.023981

    Abstract Person re-identification (re-ID) aims to match images of the same pedestrian across different cameras. It plays an important role in the field of security and surveillance. Although it has been studied for many years, it is still considered as an unsolved problem. Since the rise of deep learning, the accuracy of supervised person re-ID on public datasets has reached the highest level. However, these methods are difficult to apply to real-life scenarios because a large number of labeled training data is required in this situation. Pedestrian identity labeling, especially cross-camera pedestrian identity labeling, is heavy and expensive. Why we cannot… More >

  • Open Access

    ARTICLE

    Design of Hybrid Recommendation Algorithm in Online Shopping System

    Yingchao Wang1, Yuanhao Zhu1, Zongtian Zhang1, Huihuang Liu1,* , Peng Guo2

    Journal of New Media, Vol.3, No.4, pp. 119-128, 2021, DOI:10.32604/jnm.2021.016655

    Abstract In order to improve user satisfaction and loyalty on e-commerce websites, recommendation algorithms are used to recommend products that may be of interest to users. Therefore, the accuracy of the recommendation algorithm is a primary issue. So far, there are three mainstream recommendation algorithms, content-based recommendation algorithms, collaborative filtering algorithms and hybrid recommendation algorithms. Content-based recommendation algorithms and collaborative filtering algorithms have their own shortcomings. The contentbased recommendation algorithm has the problem of the diversity of recommended items, while the collaborative filtering algorithm has the problem of data sparsity and scalability. On the basis of these two algorithms, the hybrid… More >

  • Open Access

    ARTICLE

    The Roll Stability Analysis of Semi-Trailer Based on the Wheel Force

    Dong Wang1,*, Siwei Chen1, Weigong Zhang1, Danjie Du2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1837-1848, 2022, DOI:10.32604/cmc.2022.023033

    Abstract It is different for the liquid tank semi-trailer to keep roll stability during turning or emergency voidance, and that may cause serious accidents. Although the scholars did lots of research about the roll stability of liquid tank semi-trailer in theory by calculating and simulation, how to make an effective early warning of rollover is still unsolved in practice. The reasons include the complex driving condition and the difficulty of the vehicle parameter obtaining. The feasible method used currently is evaluating the roll stability of a liquid tank semi-trailer by the lateral acceleration or the attitude of the vehicle. Unfortunately, the… More >

  • Open Access

    ARTICLE

    Blood Pressure and Heart Rate Measurements Using Photoplethysmography with Modified LRCN

    Chih-Ta Yen1,*, Cheng-Hong Liao2

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1973-1986, 2022, DOI:10.32604/cmc.2022.022679

    Abstract In this study, single-channel photoplethysmography (PPG) signals were used to estimate the heart rate (HR), diastolic blood pressure (DBP), and systolic blood pressure (SBP). A deep learning model was proposed using a long-term recurrent convolutional network (LRCN) modified from a deep learning algorithm, the convolutional neural network model of the modified inception deep learning module, and a long short-term memory network (LSTM) to improve the model's accuracy of BP and HR measurements. The PPG data of 1,551 patients were obtained from the University of California Irvine Machine Learning Repository. How to design a filter of PPG signals and how to… More >

  • Open Access

    ARTICLE

    Switched-Beam Optimization for an Indoor Visible Light Communication Using Genetic Algorithm

    Ladathunya Pumkaew, Monthippa Uthansakul*, Peerapong Uthansakul

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1547-1566, 2022, DOI:10.32604/cmc.2022.022556

    Abstract Nowadays, Visible Light Communication (VLC) is an attractive alternative technology for wireless communication because it can use some simple Light Emitting Diodes (LEDs) instead of antennas. Typically, indoor VLC is designed to transmit only one dataset through multiple LED beams at a time. As a result, the number of users per unit of time (throughput) is relatively low. Therefore, this paper proposes the design of an indoor VLC system using switched-beam technique through computer simulation. The LED lamps are designed to be arranged in a circular array and the signal can be transmitted through the beam of each LED lamp… More >

  • Open Access

    ARTICLE

    A Study on Classification and Detection of Small Moths Using CNN Model

    Sang-Hyun Lee*

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1987-1998, 2022, DOI:10.32604/cmc.2022.022554

    Abstract Currently, there are many limitations to classify images of small objects. In addition, there are limitations such as error detection due to external factors, and there is also a disadvantage that it is difficult to accurately distinguish between various objects. This paper uses a convolutional neural network (CNN) algorithm to recognize and classify object images of very small moths and obtain precise data images. A convolution neural network algorithm is used for image data classification, and the classified image is transformed into image data to learn the topological structure of the image. To improve the accuracy of the image classification… More >

  • Open Access

    ARTICLE

    Hypo-Driver: A Multiview Driver Fatigue and Distraction Level Detection System

    Qaisar Abbas1,*, Mostafa E.A. Ibrahim1,2, Shakir Khan1, Abdul Rauf Baig1

    CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1999-2007, 2022, DOI:10.32604/cmc.2022.022553

    Abstract Traffic accidents are caused by driver fatigue or distraction in many cases. To prevent accidents, several low-cost hypovigilance (hypo-V) systems were developed in the past based on a multimodal-hybrid (physiological and behavioral) feature set. Similarly in this paper, real-time driver inattention and fatigue (Hypo-Driver) detection system is proposed through multi-view cameras and biosignal sensors to extract hybrid features. The considered features are derived from non-intrusive sensors that are related to the changes in driving behavior and visual facial expressions. To get enhanced visual facial features in uncontrolled environment, three cameras are deployed on multiview points (0°, 45°, and 90°) of… More >

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